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Revisiting Low Resource Neural Machine Translation: A Case Study

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Figure

Figure 3: BLEU scores for English-Spanish sys-tems trained on 0.4 million to 385.7 millioning curves is quite striking
Table 1: Training corpus size and subword vocabularysize for different subsets of IWSLT14 DE→EN data,and for KO→EN data.
Table 2 shows the effect of adding different meth-ods to the baseline NMT system, on the ultra-lowdata condition (100k words of training data) andthe full IWSLT 14 training corpus (3.2M words).Our ”mainstream improvements” add around 6–7BLEU in both data conditions.
Table 3: Results on full IWSLT14 German→English data on tokenized and lowercased test set with multi-bleu.perl.
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